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Percolation and Epidemic Thresholds in Clustered Networks

M. Angeles Serrano·Marian Boguna
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Abstract

We develop a theoretical approach to percolation in random clustered networks. We find that, although clustering in scale-free networks can strongly affect some percolation properties, such as the size and the resilience of the giant connected component, it cannot restore a finite percolation threshold. In turn, this implies the absence of an epidemic threshold in this class of networks extending, thus, this result to a wide variety of real scale-free networks which shows a high level of transitivity. Our findings are in good agreement with numerical simulations.

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M. Angeles Serrano, Marian Boguna. 2006-08-18. Percolation and Epidemic Thresholds in Clustered Networks. https://doi.org/10.1103/physrevlett.97.088701

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